Knowledge Discovery with Support Vector Machines

The first comprehensive overview of preprocessing, mining, and postprocessing of biological data Molecular biology is undergoing exponential growth in both the volume and complexity of biological data—and knowledge discovery offers the capacity to automate complex search and data analysis tasks. This book presents a vast overview of the most recent developments on techniques and approaches in the field of biological knowledge discovery and data mining (KDD)—providing in-depth fundamental and technical field information on the most important topics encountered. Written by top experts, Biological Knowledge Discovery Handbook: Preprocessing, Mining, and Postprocessing of Biological Data covers the three main phases of knowledge discovery (data preprocessing, data processing—also known as data mining—and data postprocessing) and analyzes both verification systems and discovery systems. BIOLOGICAL DATA PREPROCESSING Part A: Biological Data Management Part B: Biological Data Modeling Part C: Biological Feature Extraction Part D Biological Feature Selection BIOLOGICAL DATA MINING Part E: Regression Analysis of Biological Data Part F Biological Data Clustering Part G: Biological Data Classification Part H: Association Rules Learning from Biological Data Part I: Text Mining and Application to Biological Data Part J: High-Performance Computing for Biological Data Mining Combining sound theory with practical applications in molecular biology, Biological Knowledge Discovery Handbook is ideal for courses in bioinformatics and biological KDD as well as for practitioners and professional researchers in computer science, life science, and mathematics.

The purpose of this edited book is to bring together the ideas and findings of data mining researchers and bioinformaticians by discussing cutting-edge research topics such as, gene expressions, protein/RNA structure prediction, phylogenetics, sequence and structural motifs, genomics and proteomics, gene findings, drug design, RNAi and microRNA analysis, text mining in bioinformatics, modelling of biochemical pathways, biomedical ontologies, system biology and pathways, and biological database management.

Intriguing . . . [filled with] new ideas about overarching intellectual themes that govern our technologies and our society. —Nikil Jayant, Eminent Scholar, Georgia Research Alliance «Dr. Ahamed is correct in observing that 'silicon and glass have altered the rhythm of mind' and that computers need to be more 'human.'» —Bishnu S. Atal, Member, National Academy of Engineering This book combines philosophical, societal, and artificial intelligence concepts with those of computer science and information technology to demonstrate novel ways in which computers can simplify data mining on the Internet. It describes numerous innovative methods that go well beyond information retrieval to allow computers to accomplish such tasks as processing, classifying, prioritizing, and reconstituting knowledge. The book is divided into five parts: New knowledge sensing and filtering environments Concept building and wisdom machines General structure and theory of knowledge Verb functions and noun objects Humanistic and semi-human systems This book offers new mathematical methodologies and concrete HW/SW/FW configurations for the IT specialist to help their corporations explore, exploit, compete, and win global market share.

Knowledge management has become an important topic for the theory and practice of organisation management. Knowledge Coordination argues that coordination is a key factor for managing knowledge within organisations. By offering a clearcut conceptualisation of knowledge, it fills an important gap in the literature on knowledge management. Based on the authors' rational reconstruction of knowledge coordination for knowledge management, this text identifies techniques and conceptual tools to build systemic solutions to improve on corporate operational efficacy. Contrasts business strategies, and presents and discusses the tools to implement management systems based on each of the different strategies. Among these tools, the authors discuss ontological engineering, communities of practice and an original conceptual tool called Structure of Capability Providers. Covers topics including: Intelligent Agents for Knowledge Modelling Artificial Intelligence Ontologies Managing Capabilities Assessing Knowledge Coordination It will be highly popular with academic and industrial researchers who need to understand the current thinking in research of knowledge management. In addition it is aimed at senior undergraduate and postgraduate students in computer science and Information Technology and in particular researchers in knowledge engineering, artificial intelligence and agent based systems. Management and business professionals and those dealing with IT systems design and implementation will also find it useful.

To analyze complex situations we use everyday analogies that allow us to invest in an unknown domain knowledge we have acquired in a known field. In this work the author proposes a modeling and analysis method that uses the analogy of the ecosystem to embrace the complexity of an area of knowledge. After a history of the ecosystem concept and these derivatives (nature, ecology, environment ) from antiquity to the present, the analysis method based on the modeling of socio-semantic ontologies is presented, followed by practical examples of this approach in the areas of software development, digital humanities, Big Data, and more generally in the area of complex analysis.

This book makes an important contribution to our understanding of practice-based organizational learning and knowing. Based on the author's detailed study of safety practices in different corporate settings. The author uses this study to empirically describe how learning, knowing and organizing are practised. Centred on the concepts of «knowing in practice» and the «texture» of organizational knowledge. Gives a rich account of how organizations learn and how corporate practices and policies evolve.

This guide shows design practices and other construction professionals how to manage knowledge successfully. It explains how to develop and implement a knowledge management strategy, and how to avoid the pitfalls, focusing on the techniques of learning and knowledge sharing that are most relevant in professional practice. Expensive IT-based ‘solutions’ bought off-the-shelf rarely succeed in a practice context, so the emphasis here is on people-centred techniques, which recognise and meet real business knowledge needs and fit in with the organisational culture. Knowledge is supplanting physical assets as the dominant basis of capital value and an understanding of how knowledge is acquired, shared and used is increasingly crucial in organisational success. Most business leaders recognise this, but few have yet succeeded in making it the pervasive influence on management practice that it needs to become; that has turned out to be harder than it looks. Construction professionals are among those who have furthest to go, and most to gain. Design is a knowledge-based activity, and project managers, contractors and clients, as well as architects and engineers, have always learned from experience and shared their knowledge with immediate colleagues. But the intuitive processes they have traditionally used break down alarmingly quickly as organisations grow; even simply dividing the office over two floors can noticeably reduce communication. At the same time, increasingly sophisticated construction technology and more demanding markets are making effective management of knowledge ever more important. Other knowledge-intensive industries (such as management consultancy, pharmaceuticals, and IT), are well ahead in adopting a more systematic approach to learning and sharing knowledge, and seeing the benefits in improved technical capacity, efficiency, customer satisfaction and reduced risk.

A pedagogical approach to the principles and architecture of knowledge management in organizations This textbook is based on a graduate course taught at Stevens Institute of Technology. It focuses on the design and management of today’s complex K organizations. A K organization is any company that generates and applies knowledge. The text takes existing ideas from organizational design and knowledge management to enhance and elevate each through harmonization with concepts from other disciplines. The authors—noted experts in the field—concentrate on both micro- and macro design and their interrelationships at individual, group, work, and organizational levels. A key feature of the textbook is an incisive discussion of the cultural, practice, and social aspects of knowledge management. The text explores the processes, tools, and infrastructures by which an organization can continuously improve, maintain, and exploit all elements of its knowledge base that are most relevant to achieve its strategic goals. The book seamlessly intertwines the disciplines of organizational design and knowledge management and offers extensive discussions, illustrative examples, student exercises, and visualizations. The following major topics are addressed: Knowledge management, intellectual capital, and knowledge systems Organizational design, behavior, and architecture Organizational strategy, change, and development Leadership and innovation Organizational culture and learning Social networking, communications, and collaboration Strategic human resources; e.g., hiring K workers and performance reviews Knowledge science, thinking, and creativity Philosophy of knowledge and information Information, knowledge, social, strategy, and contract continuums Information management and intelligent systems; e.g., business intelligence, big data, and cognitive systems Designing Knowledge Organizations takes an interdisciplinary and original approach to assess and synthesize the disciplines of knowledge management and organizational design, drawing upon conceptual underpinnings and practical experiences in these and related areas.

Thoroughly grounded in an extensive body of international research and analysis, this book investigates the concepts surrounding a firm’s knowledge capital. These concepts play an integral part in the evolution of economic and managerial thinking, particularly in relation to the themes of firm, knowledge and innovation. The author advocates a greater socialization of the production of knowledge capital that stands in contradiction to the strong appropriation strategies that are predominant today. This book presents a historical analysis of the facts with a strong basis in the recent literature in economics and innovation management as well as in case studies of CAC 40 companies that have been conducted over the course of the past few years.

In this book a general matrix-based approach to modeling electrical machines is promulgated. The model uses instantaneous quantities for key variables and enables the user to easily take into account associations between rotating machines and static converters (such as in variable speed drives). General equations of electromechanical energy conversion are established early in the treatment of the topic and then applied to synchronous, induction and DC machines. The primary characteristics of these machines are established for steady state behavior as well as for variable speed scenarios. Important new applications for this technology (such as wind turbines, electric propulsion systems for large ships, etc.) are addressed and the book is illustrated with a large number of informative and detailed photographs, provided by various companies at the leading edge of research and applications in the field.